Sequencing the genomes of tumor cells has revealed thousands of genetic mutations linked with cancer. However, sifting through this deluge of information to figure out which of these mutations actually drive cancer growth has proven to be a tedious, time-consuming process. MIT researchers have now developed a new way to model the effects of these genetic mutations in mice. Their approach, based on the genome-editing technique known as CRISPR, is much faster than existing strategies, which require genetically engineering mice that carry the cancerous mutations.

"It's a very rapid and very adaptable approach to make models," says Thales Papagiannakopoulos, a postdoc at MIT's Koch Institute for Integrative Cancer Research and one of the lead authors of the paper, which appears in the Oct. 22 online edition of Nature. "With a lot of these mutations, we have no idea what their role is in tumor progression. If we can actually understand the biology, we can then go in and try targeted therapeutic approaches."

Led by Papagiannakopoulos, graduate student Francisco Sanchez-Rivera, the paper's other lead author, and Koch Institute director Tyler Jacks, the paper's senior author, the team used CRISPR to accurately reproduce the effects of two well-known lung cancer genes. They also modeled a gene called APC, whose role in lung cancer was not previously known.

This approach could be used to study nearly any gene in many different types of cancer, the researchers say. "There has to be a functional way of assessing the role of these cancer-gene candidates as they appear in sequencing studies," Sanchez-Rivera says. "The system we developed fills that gap immediately because you can do it very rapidly and very precisely."